Relating Microbial Community Structure to a Dominant Environmental Variable in a Complex Environment: An Example from a Chromium Contaminated Site

In a complex environment, it can be difficult to assess the degree to which a continuous variable influences microbial community structure. We propose a method that involves using the community data to "predict" the value of the presumed dominant variable. The assumption is that in order to "predict" the variable the community composition must be sensitive to or affected by the variable in question. The concentration range over which the prediction is accurate should thus provide information on the concentrations that influence community structure. We explored this approach using T-RLFP data on at a site polluted by tannery wastes. We were able to use the microbial community structure measures to predict Cr concentration over a surprisingly wide range of concentration. Although, it appears from this work that this approach can give useful information about the relationships between microbial community structure and specific environmental conditions much further testing is required.

[1]  B. Schenker,et al.  Cross-validated structure selection for neural networks , 1996 .

[2]  G. Kowalchuk,et al.  Effects of above-ground plant species composition and diversity on the diversity of soil-borne microorganisms , 2002, Antonie van Leeuwenhoek.

[3]  W. Raun,et al.  Long-term cattle manure application in soil. II. Effect on soil microbial populations and community structure , 2003, Biology and Fertility of Soils.

[4]  T. Marsh Culture-independent microbial community analysis with terminal restriction fragment length polymorphism. , 2005, Methods in enzymology.

[5]  J. Schryver,et al.  Application of Nonlinear Analysis Methods for Identifying Relationships Between Microbial Community Structure and Groundwater Geochemistry , 2006, Microbial Ecology.

[6]  T. Soule,et al.  Microbial community structure in polluted Baltic Sea sediments. , 2006, Environmental microbiology.

[7]  P. Puget,et al.  Relationship between plant and soil microbial communities along a successional gradient in a chalk grassland in north-western France , 2003 .

[8]  L. Øvreås,et al.  Microbial diversity and function in soil: from genes to ecosystems. , 2002, Current opinion in microbiology.

[9]  Marco Bosco,et al.  Soil antimony pollution and plant growth stage affect the biodiversity of auxin-producing bacteria isolated from the rhizosphere of Achillea ageratum L. , 2003, FEMS microbiology ecology.

[10]  C. Reynolds,et al.  Dissolution of metals from soils and sediments with a microwave-nitric acid digestion technique. , 1990 .

[11]  S. Chisholm,et al.  Nutrient gradients in the western North Atlantic Ocean: Relationship to microbial community structure and comparison to patterns in the Pacific Ocean , 2001 .

[12]  W. Holben,et al.  Differences in Hyporheic-Zone Microbial Community Structure along a Heavy-Metal Contamination Gradient , 2003, Applied and Environmental Microbiology.

[13]  J. Watkins,et al.  Assessing soil biodiversity across Great Britain: national trends in the occurrence of heterotrophic bacteria and invertebrates in soil. , 2003, Journal of environmental management.

[14]  J. Fry,et al.  Similarity of microbial and meiofaunal community analyses for mapping ecological effects of heavy-metal contamination in soil. , 2002, FEMS microbiology ecology.

[15]  M. Stone Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .